AWS for Industries

Strategies to Improve Inbound Detention Time in the CPG Industry

Overview of Trucking Detention Time

Inbound detention time is the time spent loading supplier goods at the warehouse, and outbound detention time is the time spent unloading goods from the warehouse and onto destination delivery trucks. Lengthy detention times have put pressure on the trucking industry for years. This has caused serious consequences to both drivers and shippers. When a driver arrives at a warehouse, the truck must be unloaded in a set amount of time. This time period varies according to the carrier. However, two hours is usually a good baseline. Anything over two hours is generally considered the “detention time.”

In this post, we will discuss detention time challenges and specific AWS services for optimizing truck unloading processes to reduce detention times.

The Importance of Reducing Detention Times for CPG Companies

Whether we’re discussing inbound or outbound transportation, lengthy detention times affect driver efficiency, shipping capacity, and safety. This all leads to negative financial impacts for the stakeholders. According to a whitepaper by J.B. Hunt Transport Services, of the 11 hours of available driving time, only 6.5 hours on average are spent on the road.

Here are challenges that stem from increased detention times:

  1. Lost driver income—Pay-by-the-mile is the most common base pay type in the trucking industry. Therefore, drivers aren’t paid during detention wait times.
  2. Increased shipping costs—Shippers must pay drivers for every hour of wait time past the standard two-hour unload timeframe.
  3. Higher loading dock labor costs—Warehouses must also pay overtime wages to dock employees who must stay late to accommodate delays.
  4. Supply chain delays—These negatively impact product availability, and cause lost retailer sales revenue and poor consumer experiences.
  5. Damaged carrier relationships—Higher costs, irritated drivers, and downstream scheduling problems.
  6. Driver safety issues—Long detention times encroach on the available waking hours for a driver, and they can increase the risk of fatigue-induced crashes.

Ways to Reduce Inbound Detention Time for CPG Companies

We’re focusing our discussion and solution on the Consumer-Packaged Goods (CPG) industry, and in particular the food, beverage, and perishable segments. This is because these CPG items typically require rapid turnaround times. However, we can extrapolate that the challenges and solutions in this post also apply to other CPG product segments, as well as entirely different industries.

Moreover, when we refer to software and data used to manage a CPG transportation fleet, we mean a fleet management system. However, when discussing software and data for managing warehouse, we mean a warehouse management system.

Now, we’ll explain several AWS solutions that can reduce inbound detention times for different CPG industry transportation situations:

Book unloading appointments, use real-time navigation, and facilitate drop-hook mechanisms

Amazon fulfillment centers and warehouses use onboarding and scheduling applications, such as Amazon Relay. Amazon Relay enables carriers to tap into the Amazon network, technology, and safety-first culture to build and grow their transportation businesses.

Drivers can book appointments to unload goods, view and manage load statuses, and report delays. Drivers can also use real-time navigation on an app via a hand-held device, such as a mobile phone. CPG companies can use this solution to improve transportation issues.

Fleet management systems such as this are integrated with warehouse management systems, and they can automate processes and let drivers use the drop-hook mechanism. With the drop-hook process, drivers drop inbound container loads and hook onto the already-loaded containers. This reduces both inbound and outbound detention times. Furthermore, the drop-hook mechanism opens dock space at the warehouse, which increases overall throughput.

Prioritize seasonal and perishable consumer goods

Some consumer goods are in high demand during specific seasons, such as candy at Halloween. CPGs and retailers must prioritize these loads over other less time-sensitive loads in the warehouse management system without causing detention delays to other drivers and incurring penalty fees. This seasonal priority approach requires more sophisticated planning capabilities than the usual first-in-first-out (FIFO) approach. This same priority also applies to perishable goods, which have a shelf life of weeks rather than months or years. A dynamic supply chain solution is one architecture type that can help plan for such variable demands.

Leverage computer vision at parking yards

AWS provides an advanced computer vision services at the edge, called AWS Panorama. This analyzes video feeds from warehouse parking yard cameras to determine the number of spots available for inbound trucks. This technology provides real-time expected wait-time notifications to inbound drivers, as well as details on which dock locations at the warehouse yard are available for parking.

Forecast peak load/unload times

Warehouses must know their peak unload and load times for workforce, inventory, and space planning. Amazon Forecast can help facilitate these operations, using the same AI-based technology as By processing Amazon Forecast data through Amazon Lambda, an event-driven compute service, and then feeding the data into a warehouse management system, managers can make data-driven decisions to fine-tune scheduling and inventory planning.

Receive real-time traffic and weather notifications

Traffic congestion can be highly unpredictable, and it is common for fleet management systems to be integrated with weather and traffic APIs for real-time updates. Moreover, this up-to-the-minute information can help warehouse managers plan for parking spots, inventory, and labor. Amazon Simple Notification Service (SNS) can help send SMS alerts to notify drivers to change routes based on weather and traffic conditions. Refer to the architecture in this post to dive deeper into this topic.

A High-Level AWS Solution to Reduce Inbound Detention Times

The following figure shows how the data from the warehouse management system flows through AWS Glue and Amazon Simple Storage Service (Amazon S3) and is eventually used for forecasting in Amazon Forecast.

  1. AWS Glue, a serverless data integration AWS service, discovers, prepares, and combines the data for Amazon Forecast.
  2. Amazon S3, the object storage service which is built to retrieve any amount of data from anywhere, is used to hold the data across its various stages.
  3. The AWS Glue workflow triggers the AWS Glue jobs for data transforms.
  4. The AWS Glue workflow also orchestrates the three steps within Forecast (load, train, and forecast).
  5. Amazon Forecast, the machine learning (ML) based forecasting service, generates a customized forecasting model for a specific use case, such as what products can cause seasonal demands and must be ordered ahead of time to reduce inbound detention times.

Figure 1: A high-level solution comprised of AWS services to reduce inbound detention times.

Optimize Transportation and Logistics Processes

We’ve all been feeling the pinch of supply chain bottlenecks lately. Regardless of the bigger issues at play, specific AWS technologies can be deployed by CPG companies, as well as supply chain, logistics, and warehouse managers, to alleviate the common challenges that typically burden the transportation and logistics industry.

If you want to discuss how these new solutions can help your organization overcome transportation and logistics issues, then AWS is here to help. Contact your AWS account team today.

Michele Sancricca

Michele Sancricca

Michele Sancricca is the AWS Worldwide Head of Technology for Transportation and Logistics. Previously he worked as Head of Supply Chain Products for Amazon Global Mile and led the Digital Transformation Division of the second largest ocean carrier in the world, Mediterranean Shipping Company. A retired Lieutenant Commander, Michele spent 12 years in the Italian Navy as Telecommunication Officer and Commanding Officer.

Alak Eswaradass

Alak Eswaradass

Alak Eswaradass is a Solutions Architect at AWS based in Chicago, Illinois. She is passionate about helping customers design cloud architectures utilizing AWS services to solve business challenges. She has a Master’s degree in computer science engineering. Before joining AWS, she worked for different healthcare organizations, and she has in-depth experience architecting complex systems, technology innovation, and research.

Shailaja Suresh

Shailaja Suresh

Shailaja Suresh is a Senior Solutions Architect at Amazon Web Services and provides prescriptive technical guidance to her customers as part of their AWS cloud journey. Her key competencies are product architecture, strategy and delivery. Her engineering skills cover a wide range of technologies and she has played the roles of being a software engineer, architect, lead and project manager. Shailaja strongly believes in empowering teams through mentorship and coaching.